Comparison of predictor sets for species richness and the number of rare species of butterflies and birds

J.R. Thomson, Erica Fleishman, R. Mac Nally, D.S. Dobkin

    Research output: Contribution to journalArticle

    18 Citations (Scopus)

    Abstract

    Aim
    Accurate inventories of biota are typically restricted to few locations within an extensive region. Accordingly, effective planning must involve some form of surrogate measures coupled with spatial modelling. We conducted a simultaneous comparison of models of both species richness and the number of rare species using three types of surrogates (indicator species, vegetation composition and structure, and topoclimate) as predictors. We evaluated each type of surrogate alone and in combination with others.

    Location
    Data for our analyses were collected from 1996–2004 in three adjacent mountain ranges in the central Great Basin (Lander and Nye counties, Nevada, USA), the Shoshone Mountains, Toiyabe Range and Toquima Range.

    Methods
    Data on species richness and species composition of butterflies and birds and measures of vegetation composition and structure were obtained in the field. Topoclimatic variables were derived by GIS from digital sources and satellite images. We used Poisson regression with Bayesian model averaging to predict species richness and the number of rare species. We compared the expected prediction success of all models on the basis of internal and external validation trials.

    Results
    Same-taxon indicator species were the most accurate predictors of species richness and of the number of rare species of butterflies and birds. Cross-taxon indicator species and topoclimate variables were reasonably accurate predictors of species richness of butterflies and birds and of the number of rare butterfly species. Although vegetation variables were more effective for predicting species richness and number of rare species of birds than of butterflies, they were the least accurate predictors overall.

    Main conclusions
    Although indicator species may provide the most accurate predictions of species richness, their practical value, like any surrogate measure, depends greatly on ecological considerations and land-use context. In general, the ability to predict numbers of rare species based on any set of candidate predictors was weaker than the ability to predict species richness, which may result from the high degree of stochasticity that often characterizes distributions of rare species. Our statistical approach for objective examination of different candidate predictors can help ensure that selection of species-richness surrogates in any system is scientifically reliable and cost-effective.
    Original languageEnglish
    Pages (from-to)90-101
    Number of pages12
    JournalJournal of Biogeography
    Volume34
    Issue number1
    DOIs
    Publication statusPublished - 2007

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    rare species
    butterfly
    butterflies
    species richness
    bird
    species diversity
    birds
    indicator species
    vegetation
    comparison
    mountains
    prediction
    stochasticity
    biota
    GIS
    planning
    land use
    basins
    indicator
    organisms

    Cite this

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    title = "Comparison of predictor sets for species richness and the number of rare species of butterflies and birds",
    abstract = "AimAccurate inventories of biota are typically restricted to few locations within an extensive region. Accordingly, effective planning must involve some form of surrogate measures coupled with spatial modelling. We conducted a simultaneous comparison of models of both species richness and the number of rare species using three types of surrogates (indicator species, vegetation composition and structure, and topoclimate) as predictors. We evaluated each type of surrogate alone and in combination with others.LocationData for our analyses were collected from 1996–2004 in three adjacent mountain ranges in the central Great Basin (Lander and Nye counties, Nevada, USA), the Shoshone Mountains, Toiyabe Range and Toquima Range.MethodsData on species richness and species composition of butterflies and birds and measures of vegetation composition and structure were obtained in the field. Topoclimatic variables were derived by GIS from digital sources and satellite images. We used Poisson regression with Bayesian model averaging to predict species richness and the number of rare species. We compared the expected prediction success of all models on the basis of internal and external validation trials.ResultsSame-taxon indicator species were the most accurate predictors of species richness and of the number of rare species of butterflies and birds. Cross-taxon indicator species and topoclimate variables were reasonably accurate predictors of species richness of butterflies and birds and of the number of rare butterfly species. Although vegetation variables were more effective for predicting species richness and number of rare species of birds than of butterflies, they were the least accurate predictors overall.Main conclusionsAlthough indicator species may provide the most accurate predictions of species richness, their practical value, like any surrogate measure, depends greatly on ecological considerations and land-use context. In general, the ability to predict numbers of rare species based on any set of candidate predictors was weaker than the ability to predict species richness, which may result from the high degree of stochasticity that often characterizes distributions of rare species. Our statistical approach for objective examination of different candidate predictors can help ensure that selection of species-richness surrogates in any system is scientifically reliable and cost-effective.",
    author = "J.R. Thomson and Erica Fleishman and {Mac Nally}, R. and D.S. Dobkin",
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    Comparison of predictor sets for species richness and the number of rare species of butterflies and birds. / Thomson, J.R.; Fleishman, Erica; Mac Nally, R.; Dobkin, D.S.

    In: Journal of Biogeography, Vol. 34, No. 1, 2007, p. 90-101.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Comparison of predictor sets for species richness and the number of rare species of butterflies and birds

    AU - Thomson, J.R.

    AU - Fleishman, Erica

    AU - Mac Nally, R.

    AU - Dobkin, D.S.

    N1 - Cited By :16 Export Date: 6 June 2017

    PY - 2007

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    N2 - AimAccurate inventories of biota are typically restricted to few locations within an extensive region. Accordingly, effective planning must involve some form of surrogate measures coupled with spatial modelling. We conducted a simultaneous comparison of models of both species richness and the number of rare species using three types of surrogates (indicator species, vegetation composition and structure, and topoclimate) as predictors. We evaluated each type of surrogate alone and in combination with others.LocationData for our analyses were collected from 1996–2004 in three adjacent mountain ranges in the central Great Basin (Lander and Nye counties, Nevada, USA), the Shoshone Mountains, Toiyabe Range and Toquima Range.MethodsData on species richness and species composition of butterflies and birds and measures of vegetation composition and structure were obtained in the field. Topoclimatic variables were derived by GIS from digital sources and satellite images. We used Poisson regression with Bayesian model averaging to predict species richness and the number of rare species. We compared the expected prediction success of all models on the basis of internal and external validation trials.ResultsSame-taxon indicator species were the most accurate predictors of species richness and of the number of rare species of butterflies and birds. Cross-taxon indicator species and topoclimate variables were reasonably accurate predictors of species richness of butterflies and birds and of the number of rare butterfly species. Although vegetation variables were more effective for predicting species richness and number of rare species of birds than of butterflies, they were the least accurate predictors overall.Main conclusionsAlthough indicator species may provide the most accurate predictions of species richness, their practical value, like any surrogate measure, depends greatly on ecological considerations and land-use context. In general, the ability to predict numbers of rare species based on any set of candidate predictors was weaker than the ability to predict species richness, which may result from the high degree of stochasticity that often characterizes distributions of rare species. Our statistical approach for objective examination of different candidate predictors can help ensure that selection of species-richness surrogates in any system is scientifically reliable and cost-effective.

    AB - AimAccurate inventories of biota are typically restricted to few locations within an extensive region. Accordingly, effective planning must involve some form of surrogate measures coupled with spatial modelling. We conducted a simultaneous comparison of models of both species richness and the number of rare species using three types of surrogates (indicator species, vegetation composition and structure, and topoclimate) as predictors. We evaluated each type of surrogate alone and in combination with others.LocationData for our analyses were collected from 1996–2004 in three adjacent mountain ranges in the central Great Basin (Lander and Nye counties, Nevada, USA), the Shoshone Mountains, Toiyabe Range and Toquima Range.MethodsData on species richness and species composition of butterflies and birds and measures of vegetation composition and structure were obtained in the field. Topoclimatic variables were derived by GIS from digital sources and satellite images. We used Poisson regression with Bayesian model averaging to predict species richness and the number of rare species. We compared the expected prediction success of all models on the basis of internal and external validation trials.ResultsSame-taxon indicator species were the most accurate predictors of species richness and of the number of rare species of butterflies and birds. Cross-taxon indicator species and topoclimate variables were reasonably accurate predictors of species richness of butterflies and birds and of the number of rare butterfly species. Although vegetation variables were more effective for predicting species richness and number of rare species of birds than of butterflies, they were the least accurate predictors overall.Main conclusionsAlthough indicator species may provide the most accurate predictions of species richness, their practical value, like any surrogate measure, depends greatly on ecological considerations and land-use context. In general, the ability to predict numbers of rare species based on any set of candidate predictors was weaker than the ability to predict species richness, which may result from the high degree of stochasticity that often characterizes distributions of rare species. Our statistical approach for objective examination of different candidate predictors can help ensure that selection of species-richness surrogates in any system is scientifically reliable and cost-effective.

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